2023 Data Science: Python for Data Analysis Full Bootcamp

Learn and build your Python Programming skills from the ground up in addition to Python Data Science libraries and tools

Created by : Rated :4.5 821 views

Last Updated: 2023-07-10 05:07:20 English Course Type: Self Learning

Code with Python Programming Language
Python Functional Programming
Structure Data using collection containers
Object-Oriented Design
Advanced Python Foundations
Handling Data with Python Libraries
Numerical Python
Extracting and Analyzing data from different resources
Data Analysis with Pandas
Data Visualization using matplotlib
Advanced Visualization with Seaborn
Build Python solutions for data science
Get Instructor QA Support and help

Hello and welcome to Data Science: Python for Data Analysis Full Bootcamp.

Data science is a huge field and one of the promising fields that is spreading in a fast way. Also, it is one of the very rewarding, and it is increasing in expansion day by day, due to its great importance and benefits, as it is the future.

Data science enables companies to measure, track, and record performance metrics for facilitating and enhancing decision-making. Companies can analyze trends to make critical decisions to engage customers better, enhance company performance, and increase profitability.

And the employment of data science and its tools depends on the purpose you want from them.

For example, using data science in health care is very different from using data science in finance and accounting, and so on. And I’ll show you the core libraries for data handling, analysis and visualization which you can use in different areas.

One of the most powerful programming languages that are used for Data science is Python, which is an easy, simple and very powerful language with many libraries and packages that facilitate working on complex and different types of data.

In this course, you will learn how to code in Python from the beginning and then you will master how to deal with the most famous libraries and tools of the Python language related to data science, starting from data collection, acquiring and analysis to visualize data with advanced techniques, and based on that, the necessary decisions are taken by companies.

I am Ahmed Ibrahim, a software engineer and Instructor and I have taught more than 500,000 engineers and developers around the world in topics related to programming languages and their applications, and in this course, we will dive deeply into the core Python fundamentals, Advanced Foundations, Data handling libraries, Numerical Python, Pandas, Matplotlib and finally Seaborn.

I hope that you will join us in this course to master the Python language for data analysis and Visualization like professionals in this field.

We have a lot to cover in this course.

Let’s get started!

No Python prior experience is required to take this Training
Computer and Internet access

Python beginners and newbies
Data Scientist who knows other language tools
New Python Data Analysts
Data Science Beginners
New developers and Programmers
Programmers and developers who know other programming language but are new to python
Anyone who wants to use Python for data analysis and visualization in a short time!

Section 1 : Course Introduction 5 Lectures 00:18:41
Lecture 1 :
Welcome to Data Science: Python for Data Analysis 2023 Full Bootcamp Preview
Lecture 2 :
Download and Install the working tools
Lecture 3 :
Jupyter Overview + Markdown in Jupyter tutorial
Lecture 4 :
Using Jupyter Notebook for coding with Python
Lecture 5 :
Using Anaconda Prompt
Section 2 : Python Basics 6 Lectures 00:53:05
Lecture 1 :
Variables and Types Tutorial
Lecture 2 :
Describe what's inside the code
Lecture 3 :
Define Blocks and Avoid IndentationError
Lecture 4 :
Strings full tutorial
Lecture 5 :
Numbers, Math and f-string tutorial
Lecture 6 :
Handling inputs and outputs
Section 3 : Python Data Structures 4 Lectures 00:46:58
Lecture 1 :
Structure Data using lists
Lecture 2 :
Structure data using tuples
Lecture 3 :
Structure Data using Dictionaries
Lecture 4 :
Structure Data using sets
Section 4 : Python Fundamentals 12 Lectures 01:14:49
Lecture 1 :
Comparing Values
Lecture 2 :
Output from Logics
Lecture 3 :
Conditional Statements
Lecture 4 :
The while loop in Python
Lecture 5 :
The for loop in Python
Lecture 6 :
Python Library Functions
Lecture 7 :
User-Defined Functions
Lecture 8 :
The lambda power
Lecture 9 :
The break statement
Lecture 10 :
The continue statement
Lecture 11 :
The for else statement
Lecture 12 :
Program to Put all together
Section 5 : OOP in Python 2 Lectures 00:22:11
Lecture 1 :
Core Python OOP: Classes and Instances
Lecture 2 :
Core Python OOP: Exploring Inheritance
Section 6 : Advanced Concepts 6 Lectures 00:32:42
Lecture 1 :
Concise Comprehensions
Lecture 2 :
Constructed modules and random
Lecture 3 :
Doing mathematics
Lecture 4 :
Doing statistics
Lecture 5 :
Errors Exploration
Lecture 6 :
Exceptions Playground
Section 7 : Python Data Handling 5 Lectures 00:26:00
Lecture 1 :
IO data in memory
Lecture 2 :
Interacting with operating system data
Lecture 3 :
Moving data files between directories
Lecture 4 :
Data will be in the trash bin
Lecture 5 :
Zipping and Unzipping Data
Section 8 : Numerical Python(NumPy) 9 Lectures 00:37:59
Lecture 1 :
NumPy Level 1
Lecture 2 :
NumPy Level 2
Lecture 3 :
NumPy Level 3
Lecture 4 :
NumPy Level 4
Lecture 5 :
NumPy Level 5
Lecture 6 :
NumPy Level 6
Lecture 7 :
NumPy Level 7
Lecture 8 :
NumPy Level 8
Lecture 9 :
NumPy Level 9
Section 9 : Data Analysis with Pandas 6 Lectures 00:21:41
Lecture 1 :
Pandas Data Analysis Level 1
Lecture 2 :
Pandas Data Analysis Level 2
Lecture 3 :
Pandas Data Analysis Level 3
Lecture 4 :
Pandas Data Analysis Level 4
Lecture 5 :
Pandas Data Analysis Level 5
Lecture 6 :
Pandas Data Analysis Level 6
Section 10 : Data Visualization with Matplotlib 7 Lectures 00:17:55
Lecture 1 :
Matplotlib Data Visualization Level 1
Lecture 2 :
Matplotlib Data Visualization Level 2
Lecture 3 :
Matplotlib Data Visualization Level 3
Lecture 4 :
Matplotlib Data Visualization Level 4
Lecture 5 :
Matplotlib Data Visualization Level 5
Lecture 6 :
Matplotlib Data Visualization Level 6
Lecture 7 :
Matplotlib Data Visualization Level 7
Section 11 : Advanced Graphics with Seaborn 7 Lectures 00:15:21
Lecture 1 :
Seaborn Statistical Graphs Level 1
Lecture 2 :
Seaborn Statistical Graphs Level 2
Lecture 3 :
Seaborn Statistical Graphs Level 3
Lecture 4 :
Seaborn Statistical Graphs Level 4
Lecture 5 :
Seaborn Statistical Graphs Level 5
Lecture 6 :
Seaborn Statistical Graphs Level 6
Lecture 7 :
Seaborn Statistical Graphs Level 7
Section 12 : Resources 5 Lectures 00:02:34
Lecture 1 :
Python Programming
Lecture 2 :
NumPy
Lecture 3 :
Pandas
Lecture 4 :
Matplotlib
Lecture 5 :
Seaborn

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Ahmed Ibrahim,

8270 Course Views

3 Courses

Ahmed Ibrahim is A Software Development Engineer | Data Science Professional | Training Content Engineer/Instructor I taught more than 700,000 students, developers and engineers from more than 190 countries around the world. - Programming Languages: Python, R, JavaScript, Java and Go. - Data Science: Data Analysis and Visualization tools and Libraries with Python, R, SQL and Spark. - Databases: Relational and Non-Relational. - Applied experience with many programming languages and tools, also a proficient knowledge and experience in Software Engineering and Data Science with skills to analyze, design and develop. - Bachelor's degree in Electrical, Communications and Computer Engineering. I always have a passion to develop my work and I like to simplify and clarify Software and Data Science skills and tools and share my skills and expertise with others via high-quality, and direct-to-point video training courses.